GlmSimulatoR

Creates Ideal Data for Generalized Linear Models

Have you ever struggled to find "good data" for a generalized linear model? Would you like to test how quickly statistics converge to parameters, or learn how picking different link functions affects model performance? This package creates ideal data for both common and novel generalized linear models so your questions can be empirically answered.

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Description file content

Package
GlmSimulatoR
Type
Package
Title
Creates Ideal Data for Generalized Linear Models
Version
0.2
Author
Greg McMahan
Maintainer
Greg McMahan
Description
Have you ever struggled to find "good data" for a generalized linear model? Would you like to test how quickly statistics converge to parameters, or learn how picking different link functions affects model performance? This package creates ideal data for both common and novel generalized linear models so your questions can be empirically answered.
License
GPL-3
Encoding
UTF-8
LazyData
true
Imports
assertthat, stats, purrr, stringr, dplyr, statmod, magrittr, rlang, ggplot2, MASS, tweedie, cplm
RoxygenNote
6.1.1
Suggests
testthat, knitr, rmarkdown, covr
VignetteBuilder
knitr
NeedsCompilation
no
Packaged
2019-11-28 19:17:19 UTC; gmcma
Repository
CRAN
Date/Publication
2019-11-28 22:10:02 UTC

install.packages('GlmSimulatoR')

0.2

16 days ago

Greg McMahan

GPL-3

Imports

assertthat, stats, purrr, stringr, dplyr, statmod, magrittr, rlang, ggplot2, MASS, tweedie, cplm

Suggests

testthat, knitr, rmarkdown, covr

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